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IJSTR >> Volume 2- Issue 9, September 2013 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Statistical Prediction Of Laser Generation For A High-Powered Copper Bromide Vapor Laser

[Full Text]



Iliycho Petkov Iliev



Index Terms: Copper bromide laser, factor analysis, nomogram, parametric model, prediction, principal component analysis, regression model.



Abstract: Based on multivariate methods of factor analysis and principal component regression, an approach is proposed for predicting the laser generation of a copper bromide vapor laser with a wavelength of 510.6 and 578.2 nm. The influence of 6 independent variables on the increase of laser output power has been considered. New values have been given to the geometric dimensions of the laser tube, the supplied electric power, and hydrogen pressure in order to improve laser generation by up to 17%. Two-dimensional nomograms with statistically valid areas in order to facilitate predictions are presented.



[1] S.E. McCoy, “Copper bromide laser treatment of facial telangiectasia: Results of patients treated over five years,” Lasers in surgery and medicine, vol. 21, no 4, pp. 329-340, 1997.

[2] I.I. Balchev, N.I. Minkovski, N.V. Sabotinov, and I.K. Kostadinov, “Micromachining with copper bromide laser,“ in: Proc. of 12th International School on Quantum Electronics: Laser Physics and Applications, P.A. Atanasov, A.A. Serafetinides and I.N. Kolev, eds., Proc. of SPIE, vol. 5226, pp. 372-376, 2003.

[3] S.I. Yakovlenko, “Gas and Plasma Lasers,” in: Encyclopedia of Low-Temperature Plasma, Series B, vol. XI(4), S.I. Yakovlenko, ed., Moscow: Fizmatlit, pp. 764-811, 2005.

[4] E. Metel, J. Podlinski, M. Dors, J. Mizeraczyk and N.V. Sabotinov, “CuBr Laser Visualization of the Bubbles Flow in a Pulsed Discharge in Water,” in: Proceedings of 14th International School on Quantum Electronics: Laser Physics and Applications, P.A. Atanasov, T.N. Dreischuh, S.V. Gateva, and L.M. Kovachev, eds, Proc. SPIE, vol. 6604, pp. 660412, 2007.

[5] S.G. Gocheva-Ilieva and I.P. Iliev, Statistical Models of Characteristics of Metal Vapor Lasers, New York: Nova Science Publ. Inc., 2011.

[6] S.G. Gocheva-Ilieva, “Application of MARS for the construction of nonparametric models,” in: Mathematics and Education in Mathematics, P. Russev, ed., Proc. of the 39th Spring Conference of the Union of Bulgarian Mathematicians, Sofia: Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, 2010, pp. 29-38, 2010. http://www.math.bas.bg/smb/2010_PK/tom/pdf/029-038.pdf

[7] I.P. Iliev, D.S. Voynikova, and S.G. Gocheva-Ilieva, “Application of the classification and regression trees for modeling the laser output power of a copper bromide vapor laser,” Math. Probl. Eng., vol. 2013, Article ID 654845, pp. 1-10, 2013. http://dx.doi.org/10.1155/2013/654845

[8] NIST/SEMATECH e-Handbook of Statistical Methods, http://www.itl.nist.gov/div898/handbook/, Accessed 30 July 2013.

[9] SPSS IBM Statistics 19, http://www-01.ibm.com/software/analytics/spss/. Accessed 30 July 2013.

[10] N.V. Sabotinov, et al., Bulg. patent No.:28674, 1975.

[11] N.V. Sabotinov, N.K. Vuchkov, and D.N. Astadjov, Gas laser discharge tube with copper halide vapors, United States Patent 4635271, 1987.

[12] I.T. Jolliffe, Principal component analysis, 2nd edition, New York: Springer, 2002.